The success rate of new sales is 6% of 200 per month, and the secret of the success of cross-border dark horses is → here
2023-08-03
Zhiyi Technology
In 2023, the tuyere of cross-border e-commerce will continue to blow, and the subdivision of cross-border clothing will become more and more vigorous.
For example, recently, giants such as TEMU and TikTok e-commerce have "overseas clones" competing to enter the game, once again setting off a wave of low-price competition, and fighting with the leading hegemon of the cross-border clothing track, the cross-border fast fashion platform SHEIN.
RecentlyZhiyi Technology visited Senbo E-commerce, a clothing e-commerce company that supplies a number of mainstream cross-border platforms。 We had an hour-long in-depth conversation with Cathy, the company's design director, and listened carefully to their experience in operating in the cross-border apparel industry. Now we will sort out and refine the key content and share it with you.
Founded in 2015, Senbo is a cross-border clothing e-commerce company, which currently owns several clothing brands such as Simplee, Glamaker, Conmoto, BIKnX, etc., covering fast fashion women's wear, plus-size women's wear, swimwear and children's wear.
In our conversations with Cathy, we learned that they supply to multiple cross-border platforms at the same time.Each brand must put at least 80 new products on the shelves every month, and with different colors, the number of new products of a single brand can even reach 1,200 per year。
Cathy's team of designers mainly supplies 3 brands, basicMore than 200 new models are developed every month, mainly by 4 fashion designers。
The huge opening volume contrasts sharply with the very small number of designers, and it is conceivable that the designers are under tremendous work pressure.When we asked curiously, Cathy explained that each designer is equipped with 1 design assistant, but the assistant is only involved in the research and development of some fabrics and accessories, and does not participate in the specific design.
Obviously, the Senbo team has implemented a set of advanced product selection workflows to ensure such an efficient opening efficiency.
Cathy then told us that she asked each designer to target 12 new models per week, select and pass models at a fixed time every week, and then focus on development. whereasThe secret to truly achieving efficient selection and transfer is that she requires designers to learn to read data。
According to Cathy:“Fashion designers should not only bury their heads in design, but also understand the market, collaborate with product planning, strengthen the ability to look at data and feedback, and learn to analyze why some models will run out.”
In the past, she would arrange clerks to manually search for collections and new products on the website every day to capture fashion trends, such as new models with a certain number of collections; Or look at the model on multiple pure overseas e-commerce websites, when the same style appears frequently on multiple platforms, they need to pay attention to it.
But here's the problemThe daily volume of new products is too large, and the manual operation is too slowIt takes at least two weeks to summarize the definitive trend of rummaging, and the time difference is fast enough for the fashion industry to produce several batches of new products.
fortunatelyAfter cooperating with Zhiyi Technology, Senbo began to use "Zhiqian" and "Overseas Exploration" products to find money and see trends in a digital way。
Pass"Overseas Prospecting", users can directly find the hot-selling and new style lists of various overseas sites.If you need more specific and accurate style sales data, in:[Merchandise Center] of "Overseas Prospecting"Filter by region, category, design details, shelf time and other subdivisions according to your needs until you find the target style。
For example, the unit price of Senbo's brand supply customers is more than 30 US dollars, and they can be there when they look at the payment【Merchandise Center】filter or search for brands,One-stop accurate and direct access to the "target style library"，You can also sort by dimensions such as sales, reviews, or priceBatch collection and export。
The specific performance of social media popularity such as INS or TikTok can also be found in:"Knowledge" or "Overseas Exploration" [Community Popularity]In the section, you can find the recent popular pictures/videos of the platform, which is used to evaluate the styles with better delivery effects and predict future market trends.
In short, after using "Overseas Exploration", the team of designers led by Cathy not only significantly improved the efficiency of finding models and looking at trends, but also obtained more comprehensive and reliable data support. In the past, the manually recorded site list and INS likes can now be exported in batches with one click, which greatly improves the convenience of the design process.
At the same time, because sufficient preliminary data can be used to carry out a smooth selection and payment process,The sales success rate of the clothing designed by the Cathy team has increased from 20% to 60%It refers to the daily average of more than 4 pieces on a single platform and more than 60% of the production and sales of the first order, which fully demonstrates the important value of "designers looking at data".
On the other hand, it's not like everything is fine with data.
Cathy emphasized: "Data is the backing, and the essence of design work still requires a lot of human judgment.She gave an exampleRoad:"Other suppliers will not deeply analyze the factors of popular models, and their model of creating 'popular models' is generally to see that a model is successful, and then start to change fabrics and patterns, and quickly evolve more similar models. But the results are often unsatisfactory, some models are easy to sell and some are not easy to sell, and there is still an element of luck.”
The crux of the problem lies in the customer's demand scenario. Designers must understand what the original popular model met the needs of consumers, and whether it still meets the needs after the facelift. If a sequined dress that was originally sold out was changed to a printed pattern, would it still fit the use scenario of the dress in the party? Will the original target audience change?
Therefore, even if you have a large amount of market sales data,Clothing design essentially has to return to the needs of consumersThe style must also have a certain aesthetic, not blindly adjust the design variables based on data.
“Clothing design should be from the perspective of consumers。 The popular style is always 1, and the style modified from the popular model is actually 0 copied downward. The current design model of Senbo is based on 1 to evolve more 1 and do horizontal innovation. ”
After straightening out the matter of "how to use data to correctly create popular models", Cathy asked designers to observe local consumer behavior and local market trends in addition to regular data such as sales volume and price to assist in the selection of models. She herself will also focus on the designer's understanding of the style and the source of the design idea in the weekly style meeting.
As a design director, Cathy also has a high demand for herself: "Every time the pre-season development or design doesn't go well, I have to go around looking at the data, watching the show, and reading hundreds of reports to judge the market trends, and summarize them into conclusions that are suitable for us." ”
Unfortunately, most of the trend reports on the market did save her a lot of time, but they were only "reference content" and could not provide "logical conclusions", for Cathy, who is good at reasoning, he needs data and trends to verify the correctness of each other, so that he can make up his mind to make decisions.
Zhiyi Technology[Report] of "Know-how"The section just meets her need for "data and trends corroborate each other". Especially the overseas cross-border trend report, only Zhiyi Technology is doing it.
As shown in the figure below, in the cross-border report of "Zhiqian", it will not only provide the popular trends of dresses, shirts and other categories, but also summarize the market share of each hot-selling attribute based on the data.Assist Cathy to better summarize the ideas of creating cross-border hits。
Based onCorrectly use data intelligence SaaS products such as "intellectual funds" and "overseas exploration".At present, from the management to the designer assistant, the whole team has established a virtuous circle of "data-driven design" from top to bottom：
The design director confirms the design direction according to the massive data, and the designer uses the data as the support to select and set the model, and prepares the clothing products with sufficient and accurate preliminary data to make the clothing products more in line with the market demand, and the success rate is greatly improved.
This data-driven design process not only greatly improves the productivity of the entire team, but also reduces inventory risk.At the same time, under the leadership of Cathy, the Senbo design team did not simply follow the trend, but gained insight into the trend direction and user preferences from the data, and achieved valuable design innovation.
After long-term accumulation, Senbo's products are becoming more and more competitive, and it is difficult to be imitated by competitors, because the core of creating a popular model lies in the design idea of using data, not just a single color or fabric.
It can be said thatData thinking has changed the way the Senbo design team works。 In the organic combination of personal experience and big data, Senbo stepped on the platform's traffic support policy to encourage differentiation.Gradually detached from the current spanThe trap of low-price competition in the clothing e-commerce industry is intensifying,Leading the way in the fierce competition in the cross-border apparel market.
As a long-term partner of Senbo e-commerce, Zhiyi Technology is also honored to provide a good working experience for the Senbo designer team。 They have achieved a double improvement in work efficiency and design quality through the use of "overseas exploration" and "knowledge of money", which once again proves the correctness of "AI helps the apparel industry".
In the future, Zhiyi Technology will continue to devote itself to technological innovation and use AI big data to empower designers and brands with a more intelligent and efficient design work experience. We will also strengthen communication with customers, deeply understand their actual needs and use feedback, and continuously iterate and optimize products and services.
We look forward to establishing long-term strategic partnerships with more excellent customers, driving the progress and development of the entire apparel design with the power of data, and injecting new momentum into the industry.
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